Training dataset measurements of immunofluorescence retina nuclear layers disclosed no significant differences between TT and any observer's average outer nuclear layer (ONL) (p = 0.998), inner nuclear layer (INL) (p = 0.807), and ONL/INL ratio (p = 0.944) measurements. In the calibration dataset, there were no differences in layer thickness between measured and known thickness masks, with an overall coefficient of variation of 0.00%. Finally, we tested the performance of TT measurements in a validation dataset of retinal detachment images.
IMAGEJ CALIBRATE MANUAL
Following, we created a training dataset and performed an agreement analysis of thickness measurements between TT and two masked manual observers. To calibrate TT, we created a calibration dataset of mock binary skeletonized mask images with increasing thickness masks and different rotations. We developed the ThicknessTool (TT), an automated thickness measurement plugin for the ImageJ platform.
Research Seminars, Conferences, and Symposia.Mobility Enhancement & Vision Rehabilitation.
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